DOI: 10.1007/s11069-021-04614-y
论文题名: Quarterly PM2.5 prediction using a novel seasonal grey model and its further application in health effects and economic loss assessment: evidences from Shanghai and Tianjin, China
作者: Wang J. ; Du P.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2021
卷: 107, 期: 1 起始页码: 889
结束页码: 909
语种: 英语
中文关键词: Economic loss assessment
; Health effects
; Quarterly PM2.5 prediction
; Seasonal grey models
英文关键词: accuracy assessment
; comparative study
; economic analysis
; economic impact
; hazard assessment
; health impact
; particulate matter
; prediction
; seasonal variation
; China
; Shanghai
; Tianjin
英文摘要: Previous research only focused on PM2.5 prediction without considering its further application or just evaluated the past years' health effects and economic losses caused by PM2.5 without studying the future scenarios. Thus, a novel hybrid system using a seasonal grey model with the fractional order accumulation, called SFGM (1, 1), and health economic loss assessment model was developed in this study, which can not only perform quarterly PM2.5 prediction, but also estimate its health effects and economic losses. The results indicated that (1) the designed SFGM (1, 1) can not only reflect the seasonal fluctuation, but also predict the seasonal PM2.5 concentrations with higher prediction accuracy in both out-and-in-samples than comparison models. (2) The total economic losses in 2020 of Shanghai and Tianjin will be 6867.25 million yuan (95% CI: 3072.34–10704.47) and 4869.20 million yuan (95% CI: 2194.50–7532.00), respectively, showing that Shanghai will suffer bigger economic losses than Tianjin. (3) The economic loss caused by the premature deaths attributable to PM2.5 is the largest, accounting for more than 70% of the total economic loss. Finally, the findings can help policymakers to formulate more policies and take effective measures to improve public awareness of environmental protection. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/169440
Appears in Collections: 气候变化与战略
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作者单位: School of Statistics, Dongbei University of Finance and Economics, Dalian, Liaoning 116025, China; School of Management, Xi′an Jiaotong University, Xi′an, 710049, China
Recommended Citation:
Wang J.,Du P.. Quarterly PM2.5 prediction using a novel seasonal grey model and its further application in health effects and economic loss assessment: evidences from Shanghai and Tianjin, China[J]. Natural Hazards,2021-01-01,107(1)